Daniel Polo — Senior Backend Engineer & Software Architect

01 — About

Systems where software meets the physical world

I'm a full-stack engineer with 10+ years of professional experience, deep on backend architecture for enterprise web applications (CRM, ERP) and industrial automation.

For the past few years I've architected management software for fully-automated warehouses — real-time integration with autonomous guided vehicles (AGVs) and precision weighing hardware through custom protocol adapters, orchestrating ~200 pick-and-place operations per day across ~20,000 SKUs.

Most recently I led a CAD automation initiative that replaced a legacy 2D AutoCAD workflow with a SolidWorks macro pipeline — generating 3D assemblies and 2D technical layouts directly from ERP data, cutting drawing time by ~99%.

Deep on the backend (Java / Spring), capable across the frontend. My focus stays on the craft of building software — growing toward architect-level backend and platform work — while I deliberately explore AI-agent engineering as the next frontier.

On visibility

Most of my strongest work is proprietary and under NDA. What's public here is purpose-built to demonstrate the same engineering — reference projects and coding challenges. I'm glad to walk through the architecture and design decisions of the private systems in a call, or share sanitised case studies.

02 — Tech

The stack I architect with

Primary stack JavaSpring BootSpring MVCPostgreSQLREST / OpenAPIDocker

Languages

JavaTypeScriptJavaScriptPythonPHPVBASQL

Frameworks & runtime

Spring BootSpring MVCNode.js

Databases

PostgreSQLMySQLOracleInformix

Tools & DevOps

DockerMavenGradleGit

CAD & automation

SolidWorks APIAutoCADPDM

API & integration

RESTOpenAPIPostmanSMTP

03 — Selected work

Three systems, built end to end

Production systems I architected and owned — backend design, data modelling, integrations, and documentation.

P-01

Robotised warehouse management system

JavaSpring BootPostgreSQLDockerREST

Enterprise web application running operations inside a fully-automated warehouse. Real-time integration with AGVs and precision scales through custom protocol adapters; orchestrates pick-and-place workflows, inventory reconciliation, and operational dashboards. I owned backend architecture, REST API design, data modelling, and system documentation across 3 years of iterative delivery.

~200operations / day · ~20,000 SKUs

System architecture

P-02

SolidWorks 3D drawing automation pipeline

VBASolidWorks APIPDMSMTP

Macro pipeline migrating a mechanical-drawing workflow from 2D AutoCAD to 3D SolidWorks. Reads structured data from the company ERP, processes parent-file configurations, and auto-generates child 3D models and their corresponding 2D layouts — with generation flags, outcome logging, and email alerting.

~99%drawing time removed · extending to full assemblies

System architecture

P-03

Enterprise LLM wiki — local AI memory

LLMOCRAI AgentsR&D

Internal proof-of-concept for a company-wide knowledge base queryable by AI agents. Ingests and indexes proprietary documentation into a local vector store so LLM agents retrieve context-aware answers without sending data to external APIs. Focus areas: RAG pipeline architecture, chunking strategies, embedding models, and agent tool-use patterns.

~98%documents leave the network · fully local

System architecture

04 — Approach

How I work, and how I grow

Design before code

Data models and interface contracts are defined and documented before the first line of implementation. I'm direct about blockers, thorough with documentation, and default to ownership — equally effective leading a project solo or contributing inside a structured team.

If I have seen further, it is by standing on the shoulders of giants.

— Isaac Newton

Real progress builds on the work of others. I treat documentation, the developer community, and AI assistants as a force-multiplier — to move faster and explore wider — while the architecture, trade-offs, and final calls stay mine.

05 — Currently exploring

Where I'm investing next

AI agent engineering

LLM orchestration, tool-use patterns, and multi-agent workflows for real production tasks.

Local LLM knowledge systems

Privacy-preserving memory layers queryable by agents, with no data leaving the network (R&D).

Cloud-native delivery

Containerisation, CI/CD pipelines, and infrastructure as code for repeatable deployments.

06 — Samples Portfolio

Public, purpose-built references

One per core language, plus a small AI build — fully independent engineering samples designed to illustrate my architectural approach.

High-Performance Memory Pool Manager (C/C++) ↗

memory-pool · custom-allocator · high-performance

A fixed-block-size O(1) memory pool for C and C++17: pre-allocates contiguous backing storage and delivers constant-time, fixed-size allocation with zero external fragmentation and zero per-block metadata overhead. Four-function C ABI plus an idiomatic C++17 wrapper, built to enterprise quality (warnings-as-errors, sanitizers, Valgrind, Doxygen). Part of the Purpose-Built References (PBR) series.

C++

07 — Library Portfolio

Enterprise-grade libraries

Enterprise-grade repositories offering production-ready libraries that improve security, reliability, and architectural consistency across systems.

C11 Systems Utility Library ↗

Systems Programming · Data Structures · Concurrency

A dependency-free, high-performance C11 systems utility library: arena/pool allocators, generic data structures, concurrency primitives, string/parsing, I/O, and diagnostics — cross-platform across Linux, macOS, and Windows, MIT-licensed.

C

08 — Mycelium LABS

Mycelium LABS echo-system

An open-source ecosystem that turns fragmented information into a living, connected, operational asset.

Mycelium LABS ↗

Open-source · Agentic Knowledge Ecosystem

Mycelium Labs is an open-source ecosystem that turns fragmented information into a living, connected, operational asset — a shared source of truth for documentation, architecture, governance, and AI agents alike.

System Design

09 — Challenge Portfolio

Code challenges

Solution sets for major coding-challenge platforms, showcasing algorithmic rigor and clean engineering patterns.

Coding Challenges ↗

Algorithms · Problem solving

A curated list of LeetCode and similar solutions — the daily practice behind the architecture.

List

10 — Professional Portfolio

Public, Production-Grade Systems

A curated collection of real-world engineering initiatives spanning enterprise software, industrial automation, logistics platforms, and AI-enabled systems.

Enterprise Agentic Delivery Operating System (EADOS) ↗

agentic-os · project-scaffolding · code-generation

A language-agnostic agentic OS that reproduces an enterprise engineering system for any new project, in any language. It interviews the maintainer, records the answers in a single manifest, and renders a fully governed, enterprise-grade repository from parameterized templates — agent contract (AGENTS.md), ADRs, a CI quality-gate matrix, a cross-artifact consistency lint, SemVer release governance, and opt-in i18n — for any of 19 toolchains (C/C++, C#, Java, Kotlin, Scala, Python, Go, Rust, TypeScript, Swift, and more). Reverse-engineered from the pbr-cpp-memory-pool reference.

Python

11 — Blog

Notes on AI, software, and the craft

View all posts

12 — Contact

Open to fullstack & platform roles

In companies focused on product development, innovation, and advanced engineering — remote, or relocation outside Europe. I'm glad to walk through the architecture and decisions behind the private systems in a call.

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